Despite the health benefits of physical activity, many older adults living in long-term care facilities lead sedentary lifestyles and do not meet minimum physical activity recommendations. Determining the behavior change techniques (BCTs) used in physical activity interventions can help us understand the underlying mechanisms by which behavioral change is achieved. The purpose of this systematic review was to identify and evaluate BCTs in physical activity interventions for the elderly residents. Six electronic databases were searched and 15 eligible studies were retained. Nine promising BCTs associated with physical activity promotion among elderly residents were identified: credible source, social support (unspecified), goal setting (outcome), goal setting (behavior), demonstration of the behavior, instruction on how to perform a behavior, self-monitoring of behavior, self-monitoring of outcome(s) of behavior, and adding objects to the environment. Future research is encouraged to select and tailor these BCTs to the specific needs and preferences of the target population.

BACKGROUND: With the development of emerging technologies, digital behavior change interventions (DBCIs) help to maintain regular physical activity in daily life.
OBJECTIVE: To comprehensively understand the design implementations of habit formation techniques in current DBCIs, a systematic review was conducted to investigate the implementations of behavior change techniques, types of habit formation techniques, and design strategies in current DBCIs.
METHODS: The process of this review followed the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases were systematically searched from 2012 to 2022, which included Web of Science, Scopus, ACM Digital Library, and PubMed. The inclusion criteria encompassed studies that used digital tools for physical activity, examined behavior change intervention techniques, and were written in English.
RESULTS: A total of 41 identified research articles were included in this review. The results show that the most applied behavior change techniques were the self-monitoring of behavior, goal setting, and prompts and cues. Moreover, habit formation techniques were identified and developed based on intentions, cues, and positive reinforcement. Commonly used methods included automatic monitoring, descriptive feedback, general guidelines, self-set goals, time-based cues, and virtual rewards.
CONCLUSIONS: A total of 32 commonly design strategies of habit formation techniques were summarized and mapped to the proposed conceptual framework, which was categorized into target-mediated (generalization and personalization) and technology-mediated interactions (explicitness and implicitness). Most of the existing studies use the explicit interaction, aligning with the personalized habit formation techniques in the design strategies of DBCIs. However, implicit interaction design strategies are lacking in the reviewed studies. The proposed conceptual framework and potential solutions can serve as guidelines for designing strategies aimed at habit formation within DBCIs.

OBJECTIVE: The objectives were to assess (i) the quality of theory implementation, (ii) the application of behavior change techniques, and (iii) the effectiveness of theory-based interventions in promoting physical activity in pregnant women and improving maternal and neonatal outcomes.
METHODS: A systematic search was conducted across 8 databases (Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, EMBASE, MEDLINE, APA PsycINFO, PubMed, SPORTDiscus, and Web of Science) to identify randomized controlled trials published from database inception to 8 July 2023. The Cochrane risk-of-bias 2.0 tool was used to evaluate the quality of the included studies. The theory coding scheme was used to measure the quality of theory implementation, and behavior change techniques were coded according to behavior change taxonomy (version 1). The meta-analysis was performed using RevMan 5.3. The Grading of Recommendations, Assessment, Development, and Evaluation Approach was used to assess the certainty of evidence.
RESULTS: Eleven studies met the study criteria. Nine studies were based on one theory, while two studies were based on a combination of two theories. The quality of theory implementation was generally moderate. A total of 24 unique behavior change techniques were extracted. The most commonly used types of behavior change techniques were \'instruction on how to perform the behavior\' (n = 9), \'goal setting\' (behavior) (n = 8), \'action planning\' (n = 7), and \'information about health consequences\' (n = 7). Theory-based interventions significantly improved moderate-to-vigorous physical activity (standardized mean difference (SMD) = 0.17, 95 % confidence interval (CI) [0.04, 0.30], P = 0.01; moderate certainty of evidence), reduced the average gestational weight gain per week (mean difference (MD) = -0.06, 95 % CI [-0.11, -0.01], P = 0.02; moderate certainty of evidence), and decreased the incidence of gestational diabetes mellitus (risk ratio (RR) = 0.64, 95 % CI [0.46, 0.89], P = 0.008; high certainty of evidence). However, the effects of theory-based interventions on total physical activity, total gestational weight gain and the incidence of gestational hypertension and preterm delivery were unclear (P > 0.05).
CONCLUSIONS: (i) Most of the studies exhibited a moderate level of theory implementation quality. (ii) The use of theories varies, but common behavior change techniques were found across studies. (iii) Theory-based interventions can improve physical activity and maternal and neonatal outcomes and appear to be safe. Appropriate health behavior theories and behavior change techniques should be fully utilized in future interventions.
BACKGROUND: PROSPERO: CRD42023440886.
CONCLUSIONS: Theory-based interventions can improve physical activity and maternal and neonatal outcomes and appear to be safe. Appropriate health behavior theories and behavior change techniques should be fully utilized in the development of future interventions.

BACKGROUND: Women are more likely to develop breast cancer if their first-degree relatives (FDRs) have the disease, but they are often unaware of their individual risk and conduct screening behaviors.
OBJECTIVE: This study aimed to evaluate the effectiveness of interventions in increasing breast self-examination, clinical breast examination, and mammography rates in FDRs of breast cancer patients.
METHODS: We selected randomized clinical trials and quasi-experimental studies in eight databases. Interventions in each study were categorized as \"promising\", or \"non-promising\" according to whether they led to a positive change in screening behaviors. Interventions were also coded using the Behavioral Change Techniques (BCTs) Taxonomy and a promise ratio calculated for each. BCTs with a promise ratio ≥2 was classified as \"promising\".
RESULTS: Thirteen studies with 21 different BCTs were included. The most frequent BCTs were \"Prompts/cues\", \"Credible source\", and \"Instructions on how to perform the behavior\". Seven BCTs had a promise ratio of ≥2 and the four most promising were \"Information about health consequences\" (promise ratio = 6), \"Problem solving\" (promise ratio = 4), \"Demonstration of the behavior\" (promise ratio = 4), and \"Adding objects to the environment\" (promise ratio = 4).
CONCLUSIONS: This review indicated an overall weak use of theory, and an insufficient description of several interventions to support the assessment of how specific BCTs were activated.

This article presents a systematic review on autism care, diagnosis, and intervention based on mobile apps running on smartphones and tablets. Here, the term \"intervention\" means a carefully planned set of activities with the objective of improving autism symptoms. We guide our review on related studies using five research questions. First, who benefits the most from these mobile apps? Second, what are the primary purposes of these mobile apps? Third, what mechanisms have been incorporated in these mobiles apps to improve usability? Fourth, what guidelines have been used in the design and implementation of these mobile apps? Fifth, what theories and frameworks have been used as the foundation for these mobile apps to ensure the intervention effectiveness? As can be seen from these research questions, we focus on the usability and software development of the mobile apps. Informed by the findings of these research questions, we propose a taxonomy for the mobile apps and their users. The mobile apps can be categorized into autism support apps, educational apps, teacher training apps, parental support apps, and data collection apps. The individuals with autism spectrum disorder (ASD) are the primary users of the first two categories of apps. Teachers of children with ASD are the primary users of the teacher training apps. Parents are the primary users of the parental support apps, while individuals with ASD are usually the primary users of the data collection apps and clinicians and autism researchers are the beneficiaries. Gamification, virtual reality, and autism-specific mechanisms have been used to improve the usability of the apps. User-centered design is the most popular approach for mobile app development. Augmentative and alternative communication, video modeling, and various behavior change practices have been used as the theoretical foundation for intervention efficacy.

OBJECTIVE: To investigate the effect of behavior change technology on diet, exercise, and sedentary behaviors in colorectal cancer over the last decade.
METHODS: This study systematically searched six English databases (Cochrane Library, EMBASE, APA PsycInfo, SCOPUS, PubMed, Web of Science) and three Chinese databases (CNKI, WanFang, and SINOMEd), searched for eligible clinical trials published between January 1, 2012, and December 31, 2021. Each database follows the principle of PICOS and adopts the method of subject words combined with free words to conduct literature retrieval, such as \"colorectal cancer\" and \"behavior change intervention.\" Meta-analysis was performed using RevMan 5.3 software. Continuous data using the same measurement tools were analyzed using weighted mean difference (MD). Otherwise, standard mean difference (SMD) was used for analysis. The confidence interval is 95%. There was no significant statistical heterogeneity between the studies (P > 0.1, I2 < 50%), and fixed-effects model was used. There was statistical heterogeneity (P ≤ 0.1), I2 ≥ 50%), and the random effects model was used for analysis. The Cochrane risk of bias tool was used to assess the risk of bias in the included studies.
RESULTS: In total, 15 good-quality randomized controlled trials were identified. Six studies focused on eating habits. Twelve studies focused on physical activity. We found that behavior change techniques had significant effects on colorectal cancer survivors\' eating behaviors such as frequency of fruit and vegetable intake and mastery of dietary knowledge (P < 0.05). The meta-analysis showed that the amount of physical activity in the intervention group increased by 71.76 min/w (16.27 to 127.24, P = 0.01) at 3 months after treatment compared with the control group. The meta-analysis showed that the amount of physical activity in the intervention group increased by 113.97 min/w (48.34 to 179.59, P < 0.001) at 6 months after treatment compared with the control group. The results revealed significant difference in the overall effect of the behavior change technique on the amount of exercise. Behavior change techniques were not found to have significant effects on body weight and BMI in colorectal cancer survivors, but it had a significant effect on sedentary behavior (P < 0.05).
CONCLUSIONS: The effects of behavioral change technique intervention on diet and physical activity may be more clinically significant at 6 months. This is the first systematic review and meta-analysis to summarize the effectiveness of a behavioral change techniques health behavior intervention in patients with colorectal cancer.

Insufficient physical activity (PA) has been identified as a leading risk factor for premature and all-cause death, as well as non-communicable diseases. Employees, especially those with low occupational PA, are more vulnerable to physical inactivity, and studies in this population are scarce. However, employees may receive benefits for both health and work productivity from PA. Therefore, well-designed behavior change studies to promote PA in employees are urgently needed, especially during the COVID-19 pandemic. Literature was searched before 30 July 2022, and updated evidence was summarized. This review elaborates on the evidence related to insufficient PA and further provides an overview of theory-based interventions for promoting PA. Evidence indicates that intervention mapping (IM) was a useful tool to develop, implement, and evaluate behavior change interventions. Based on the IM framework, reviewing the theory- and evidence-based change methods and delivery modes, and further identifying the research gaps and limitations of existing interventions could provide promising suggestions and directions for development of well-founded interventions promoting PA among employees. The updated knowledge base for developing future interventions may boost efficacy and provide firm conclusions for researchers in this area.

BACKGROUND: The current college lifestyle create more opportunities for students to develop unhealthy behaviors, especially physical inactivity. Nudging could be an effective tool to improve physical activity behaviors by changing college settings. One-nudge-fits-all leads to ineffective nudges, so it is necessary to develop a reliable and valid instrument capable of measuring the \"nudgeability\" of physical activity nudges for college students, which is for a higher level of nudge efficacy.
METHODS: Developing the College Physical Activity Nudges Susceptibility Scale (CPANSS) that integrated the nudge method with the Likert scale, which is the first attempt to measure the susceptibility to nudges directly by a scale. There are four steps for developing CPANSS, including Scale Dimensions, Item Generation, Exploratory Factor Analysis (n = 294), and Confirmatory Factor Analysis (n = 293) with appropriate procedures.
RESULTS: The five-factor 21-item CPANSS with good reliability and validity fitted the data reasonably well.
CONCLUSIONS: The CPANSS was to provide a new tool for policymakers to design effective nudges in changing and promoting physical activity in college settings, and to provide a method for scholars to promote other healthy behaviors for different target groups.